'clarification' 검색 결과

제작 방향, 내용 구성, 납품 형식에 영향을 주는 미확인 사항을 최소한의 질문 양식으로 정리합니다. 선택 항목과 입력란으로 작업 재개에 필요한 답변을 모읍니다.

• 제작을 막는 미확인 요구 사항 확인
• 정해지지 않은 대상 독자 확인
• 납품 형식 결정

Clarify unresolved product decisions before implementation, such as scope, supported platforms, or API agreements. Use a small set of focused questions to establish the intended outcome, while leaving routine technical choices to the agent.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarify an unresolved product scope
• Confirm which platforms a product should support
• Resolve open decisions about data or API agreements

Take an idea or issue through requirements clarification, reviewed planning, implementation, and verification. Supervise all stages in one recoverable OMX workflow, preserving artifacts and progress so work can resume or return to planning when findings require changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Deliver an issue from requirements clarification through verification
• Turn an initial idea into a reviewed implementation plan
• Resume interrupted work from its saved phase

Lets an agent ask for clarification, preferences, or approval through an on-screen dialog. Questions can offer single or multiple choices and custom text input, giving the agent a user response to guide its next step.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarifying an ambiguous task
• Choosing how to organize files
• Confirming deletion or email sending

Keep implementation work moving by turning routine uncertainty into explicit assumptions. The agent follows existing project patterns, makes small reversible changes, validates results, and reports its decisions, completed changes, checks, and remaining risks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Continue implementation while away
• Reduce routine clarification stops
• Review autonomous decisions and validation results

Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Compress planner candidate questions into a compact frontdesk-facing clarification batch and normalize answers back to planner.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

The research-domain clarification skill — find underspecified items in a thesis spec.md (prose wrong_if, universe rows without rationale, missing budget/expiry/pins, ambiguous pillars), ask the human structured questions WITH options (max 5 per round), encode the answers back into spec.md's Clarifications section, and re-evaluate checklists/thesis-quality.md after every write (Q32 bidirectional maintenance).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate targeted clarifying questions (2-3 max) that challenge vague requirements and extract missing context. Use after request-analyzer identifies clarification needs, before routing to specialist agents. Helps cto-orchestrator avoid delegating unclear requirements.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reads two or more supplier, bid or tender responses against a requirements list and returns a DRAFT comparison pack: a requirement-by-supplier matrix, gaps per supplier, clarification questions and neutral observations, for an evaluation panel. Never scores, weights, ranks or recommends a winner; the award stays with the panel. Use when the user asks to "compare these bids", "matrix the tender responses against our requirements", "collate the RFQ replies", "show me where each supplier falls short" or "draft clarification questions for the bidders". Do not use for scoring or weighting against agreed criteria, use supplier-evaluation-matrix instead, or for writing the requirements, use rfp-requirements-pack instead. Drafts for human review; never approves, authorises or signs off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Implement pending tasks from an OpenSpec change using its specifications and design documents. The skill updates task checkboxes, confirms progress, supports resuming unfinished work, and pauses when requirements or implementation issues need clarification.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Start implementing a planned OpenSpec change
• Resume partially completed implementation
• Track completed and remaining tasks

Shape agent collaboration around focused clarification, practical options, and small steps that can be checked. This profile emphasizes early drafts, preserving the user's intent, and turning agreed direction into concrete outputs through iteration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Start with a draft and refine it together
• Clarify blockers with a focused question
• Compare practical options and tradeoffs

Compare a job posting with your experience to score how well the requirements match. Identify strengths, missing qualifications, and potential concerns, then plan application priorities, resume adjustments, and points to address in a cover letter.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare a job's requirements with your experience
• Prioritize jobs before preparing applications
• Plan resume adjustments and cover letter points

Looks up a person's identity, role, and relationship before asking the user for clarification. Searches stored knowledge and connected records, then the web, updates incomplete pages, and asks a specific question with a hypothesis when evidence remains inconclusive.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identifying contacts from existing records
• Filling role and relationship fields after imports
• Adding context to names in meeting preparation

Review captured agent sessions related to a GitButler branch, pull request, or change. Start with a chronological overview of previous discussions and actions, then inspect specific turns when the rationale or supporting evidence needs clarification.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Catch up on previous work on the current branch
• Review discussions related to a pull request
• Understand the reasons behind earlier changes

Supports analysis of tables already in the workspace through data inspection, Python calculations, and charts chosen for the question. It also explains how to ask users for clarification and label results with meaningful units and names.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inspecting table columns, statistics, and sample rows
• Comparing categories or tracking changes over time
• Exploring distributions and relationships

Read existing code to reconstruct system specifications, including architecture, data flows, APIs, and business rules. Produces documentation tied to code locations, separating observed behavior from inferences and questions that need clarification.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understand an undocumented legacy system
• Document existing APIs and business rules
• Map module dependencies and data flows

Prepare a structured JSON handoff for feature work, bringing together requirements, design decisions, key user journeys, tests, demo recordings, and pull request status. Clearly distinguish completed work from missing validation, publication steps, and other remaining tasks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a final handoff for feature development
• Linking key user journeys to tests and demo recordings
• Reporting unpublished work and remaining validation

Define a consistent process for unattended AI research using public sources. Limit clarification questions, show a search plan, distinguish facts from interpretations and assumptions, and keep reports structured so repeated investigations can be compared.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Defining a process for recurring competitive research
• Separating sourced facts from AI interpretations
• Comparing findings across quarterly investigations

Clean up DeepChat's specification-driven development documents after implementation and validation. Review feature, issue, and architecture files, remove completed or obsolete material when evidence supports deletion, and preserve maintained specifications while checking references.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Remove issue documents after confirming a bug is resolved
• Clear old plans from completed feature work
• Update or remove architecture documents after replacement

Review a pull request for code quality, correctness, security, tests, and documentation. Receive structured findings ranked by severity, with file references, approval status, positive highlights, and questions that need clarification.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a pull request before merging
• Checking changes against the original plan
• Auditing error handling and validation of AI output

Collect product feedback, usage data, runtime errors, and issue reports from configured sources. Classify and group findings with supporting evidence, then apply separate project rules for implementing fixes, requesting clarification, or closing reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Triage feedback from multiple sources
• Group related error reports
• Check collection coverage and unavailable sources

Draft CCB workflow task packets, readiness recommendations, and candidate clarification questions without mutating authoritative state.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.